#[non_exhaustive]pub struct InstanceRecommendationBuilder { /* private fields */ }
Expand description
A builder for InstanceRecommendation
.
Implementations§
Source§impl InstanceRecommendationBuilder
impl InstanceRecommendationBuilder
Sourcepub fn instance_arn(self, input: impl Into<String>) -> Self
pub fn instance_arn(self, input: impl Into<String>) -> Self
The Amazon Resource Name (ARN) of the current instance.
Sourcepub fn set_instance_arn(self, input: Option<String>) -> Self
pub fn set_instance_arn(self, input: Option<String>) -> Self
The Amazon Resource Name (ARN) of the current instance.
Sourcepub fn get_instance_arn(&self) -> &Option<String>
pub fn get_instance_arn(&self) -> &Option<String>
The Amazon Resource Name (ARN) of the current instance.
Sourcepub fn account_id(self, input: impl Into<String>) -> Self
pub fn account_id(self, input: impl Into<String>) -> Self
The Amazon Web Services account ID of the instance.
Sourcepub fn set_account_id(self, input: Option<String>) -> Self
pub fn set_account_id(self, input: Option<String>) -> Self
The Amazon Web Services account ID of the instance.
Sourcepub fn get_account_id(&self) -> &Option<String>
pub fn get_account_id(&self) -> &Option<String>
The Amazon Web Services account ID of the instance.
Sourcepub fn instance_name(self, input: impl Into<String>) -> Self
pub fn instance_name(self, input: impl Into<String>) -> Self
The name of the current instance.
Sourcepub fn set_instance_name(self, input: Option<String>) -> Self
pub fn set_instance_name(self, input: Option<String>) -> Self
The name of the current instance.
Sourcepub fn get_instance_name(&self) -> &Option<String>
pub fn get_instance_name(&self) -> &Option<String>
The name of the current instance.
Sourcepub fn current_instance_type(self, input: impl Into<String>) -> Self
pub fn current_instance_type(self, input: impl Into<String>) -> Self
The instance type of the current instance.
Sourcepub fn set_current_instance_type(self, input: Option<String>) -> Self
pub fn set_current_instance_type(self, input: Option<String>) -> Self
The instance type of the current instance.
Sourcepub fn get_current_instance_type(&self) -> &Option<String>
pub fn get_current_instance_type(&self) -> &Option<String>
The instance type of the current instance.
Sourcepub fn finding(self, input: Finding) -> Self
pub fn finding(self, input: Finding) -> Self
The finding classification of the instance.
Findings for instances include:
-
Underprovisioned
—An instance is considered under-provisioned when at least one specification of your instance, such as CPU, memory, or network, does not meet the performance requirements of your workload. Under-provisioned instances may lead to poor application performance. -
Overprovisioned
—An instance is considered over-provisioned when at least one specification of your instance, such as CPU, memory, or network, can be sized down while still meeting the performance requirements of your workload, and no specification is under-provisioned. Over-provisioned instances may lead to unnecessary infrastructure cost. -
Optimized
—An instance is considered optimized when all specifications of your instance, such as CPU, memory, and network, meet the performance requirements of your workload and is not over provisioned. For optimized resources, Compute Optimizer might recommend a new generation instance type.
The valid values in your API responses appear as OVER_PROVISIONED, UNDER_PROVISIONED, or OPTIMIZED.
Sourcepub fn set_finding(self, input: Option<Finding>) -> Self
pub fn set_finding(self, input: Option<Finding>) -> Self
The finding classification of the instance.
Findings for instances include:
-
Underprovisioned
—An instance is considered under-provisioned when at least one specification of your instance, such as CPU, memory, or network, does not meet the performance requirements of your workload. Under-provisioned instances may lead to poor application performance. -
Overprovisioned
—An instance is considered over-provisioned when at least one specification of your instance, such as CPU, memory, or network, can be sized down while still meeting the performance requirements of your workload, and no specification is under-provisioned. Over-provisioned instances may lead to unnecessary infrastructure cost. -
Optimized
—An instance is considered optimized when all specifications of your instance, such as CPU, memory, and network, meet the performance requirements of your workload and is not over provisioned. For optimized resources, Compute Optimizer might recommend a new generation instance type.
The valid values in your API responses appear as OVER_PROVISIONED, UNDER_PROVISIONED, or OPTIMIZED.
Sourcepub fn get_finding(&self) -> &Option<Finding>
pub fn get_finding(&self) -> &Option<Finding>
The finding classification of the instance.
Findings for instances include:
-
Underprovisioned
—An instance is considered under-provisioned when at least one specification of your instance, such as CPU, memory, or network, does not meet the performance requirements of your workload. Under-provisioned instances may lead to poor application performance. -
Overprovisioned
—An instance is considered over-provisioned when at least one specification of your instance, such as CPU, memory, or network, can be sized down while still meeting the performance requirements of your workload, and no specification is under-provisioned. Over-provisioned instances may lead to unnecessary infrastructure cost. -
Optimized
—An instance is considered optimized when all specifications of your instance, such as CPU, memory, and network, meet the performance requirements of your workload and is not over provisioned. For optimized resources, Compute Optimizer might recommend a new generation instance type.
The valid values in your API responses appear as OVER_PROVISIONED, UNDER_PROVISIONED, or OPTIMIZED.
Sourcepub fn finding_reason_codes(
self,
input: InstanceRecommendationFindingReasonCode,
) -> Self
pub fn finding_reason_codes( self, input: InstanceRecommendationFindingReasonCode, ) -> Self
Appends an item to finding_reason_codes
.
To override the contents of this collection use set_finding_reason_codes
.
The reason for the finding classification of the instance.
Finding reason codes for instances include:
-
CPUOverprovisioned
— The instance’s CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theCPUUtilization
metric of the current instance during the look-back period. -
CPUUnderprovisioned
— The instance’s CPU configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better CPU performance. This is identified by analyzing theCPUUtilization
metric of the current instance during the look-back period. -
MemoryOverprovisioned
— The instance’s memory configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the memory utilization metric of the current instance during the look-back period. -
MemoryUnderprovisioned
— The instance’s memory configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better memory performance. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.Memory utilization is analyzed only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling memory utilization with the Amazon CloudWatch Agent in the Compute Optimizer User Guide. On Linux instances, Compute Optimizer analyses the
mem_used_percent
metric in theCWAgent
namespace, or the legacyMemoryUtilization
metric in theSystem/Linux
namespace. On Windows instances, Compute Optimizer analyses theMemory % Committed Bytes In Use
metric in theCWAgent
namespace. -
EBSThroughputOverprovisioned
— The instance’s EBS throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theVolumeReadBytes
andVolumeWriteBytes
metrics of EBS volumes attached to the current instance during the look-back period. -
EBSThroughputUnderprovisioned
— The instance’s EBS throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS throughput performance. This is identified by analyzing theVolumeReadBytes
andVolumeWriteBytes
metrics of EBS volumes attached to the current instance during the look-back period. -
EBSIOPSOverprovisioned
— The instance’s EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theVolumeReadOps
andVolumeWriteOps
metric of EBS volumes attached to the current instance during the look-back period. -
EBSIOPSUnderprovisioned
— The instance’s EBS IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS IOPS performance. This is identified by analyzing theVolumeReadOps
andVolumeWriteOps
metric of EBS volumes attached to the current instance during the look-back period. -
NetworkBandwidthOverprovisioned
— The instance’s network bandwidth configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theNetworkIn
andNetworkOut
metrics of the current instance during the look-back period. -
NetworkBandwidthUnderprovisioned
— The instance’s network bandwidth configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network bandwidth performance. This is identified by analyzing theNetworkIn
andNetworkOut
metrics of the current instance during the look-back period. This finding reason happens when theNetworkIn
orNetworkOut
performance of an instance is impacted. -
NetworkPPSOverprovisioned
— The instance’s network PPS (packets per second) configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theNetworkPacketsIn
andNetworkPacketsIn
metrics of the current instance during the look-back period. -
NetworkPPSUnderprovisioned
— The instance’s network PPS (packets per second) configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network PPS performance. This is identified by analyzing theNetworkPacketsIn
andNetworkPacketsIn
metrics of the current instance during the look-back period. -
DiskIOPSOverprovisioned
— The instance’s disk IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theDiskReadOps
andDiskWriteOps
metrics of the current instance during the look-back period. -
DiskIOPSUnderprovisioned
— The instance’s disk IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk IOPS performance. This is identified by analyzing theDiskReadOps
andDiskWriteOps
metrics of the current instance during the look-back period. -
DiskThroughputOverprovisioned
— The instance’s disk throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theDiskReadBytes
andDiskWriteBytes
metrics of the current instance during the look-back period. -
DiskThroughputUnderprovisioned
— The instance’s disk throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk throughput performance. This is identified by analyzing theDiskReadBytes
andDiskWriteBytes
metrics of the current instance during the look-back period.
For more information about instance metrics, see List the available CloudWatch metrics for your instances in the Amazon Elastic Compute Cloud User Guide. For more information about EBS volume metrics, see Amazon CloudWatch metrics for Amazon EBS in the Amazon Elastic Compute Cloud User Guide.
Sourcepub fn set_finding_reason_codes(
self,
input: Option<Vec<InstanceRecommendationFindingReasonCode>>,
) -> Self
pub fn set_finding_reason_codes( self, input: Option<Vec<InstanceRecommendationFindingReasonCode>>, ) -> Self
The reason for the finding classification of the instance.
Finding reason codes for instances include:
-
CPUOverprovisioned
— The instance’s CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theCPUUtilization
metric of the current instance during the look-back period. -
CPUUnderprovisioned
— The instance’s CPU configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better CPU performance. This is identified by analyzing theCPUUtilization
metric of the current instance during the look-back period. -
MemoryOverprovisioned
— The instance’s memory configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the memory utilization metric of the current instance during the look-back period. -
MemoryUnderprovisioned
— The instance’s memory configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better memory performance. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.Memory utilization is analyzed only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling memory utilization with the Amazon CloudWatch Agent in the Compute Optimizer User Guide. On Linux instances, Compute Optimizer analyses the
mem_used_percent
metric in theCWAgent
namespace, or the legacyMemoryUtilization
metric in theSystem/Linux
namespace. On Windows instances, Compute Optimizer analyses theMemory % Committed Bytes In Use
metric in theCWAgent
namespace. -
EBSThroughputOverprovisioned
— The instance’s EBS throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theVolumeReadBytes
andVolumeWriteBytes
metrics of EBS volumes attached to the current instance during the look-back period. -
EBSThroughputUnderprovisioned
— The instance’s EBS throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS throughput performance. This is identified by analyzing theVolumeReadBytes
andVolumeWriteBytes
metrics of EBS volumes attached to the current instance during the look-back period. -
EBSIOPSOverprovisioned
— The instance’s EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theVolumeReadOps
andVolumeWriteOps
metric of EBS volumes attached to the current instance during the look-back period. -
EBSIOPSUnderprovisioned
— The instance’s EBS IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS IOPS performance. This is identified by analyzing theVolumeReadOps
andVolumeWriteOps
metric of EBS volumes attached to the current instance during the look-back period. -
NetworkBandwidthOverprovisioned
— The instance’s network bandwidth configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theNetworkIn
andNetworkOut
metrics of the current instance during the look-back period. -
NetworkBandwidthUnderprovisioned
— The instance’s network bandwidth configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network bandwidth performance. This is identified by analyzing theNetworkIn
andNetworkOut
metrics of the current instance during the look-back period. This finding reason happens when theNetworkIn
orNetworkOut
performance of an instance is impacted. -
NetworkPPSOverprovisioned
— The instance’s network PPS (packets per second) configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theNetworkPacketsIn
andNetworkPacketsIn
metrics of the current instance during the look-back period. -
NetworkPPSUnderprovisioned
— The instance’s network PPS (packets per second) configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network PPS performance. This is identified by analyzing theNetworkPacketsIn
andNetworkPacketsIn
metrics of the current instance during the look-back period. -
DiskIOPSOverprovisioned
— The instance’s disk IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theDiskReadOps
andDiskWriteOps
metrics of the current instance during the look-back period. -
DiskIOPSUnderprovisioned
— The instance’s disk IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk IOPS performance. This is identified by analyzing theDiskReadOps
andDiskWriteOps
metrics of the current instance during the look-back period. -
DiskThroughputOverprovisioned
— The instance’s disk throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theDiskReadBytes
andDiskWriteBytes
metrics of the current instance during the look-back period. -
DiskThroughputUnderprovisioned
— The instance’s disk throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk throughput performance. This is identified by analyzing theDiskReadBytes
andDiskWriteBytes
metrics of the current instance during the look-back period.
For more information about instance metrics, see List the available CloudWatch metrics for your instances in the Amazon Elastic Compute Cloud User Guide. For more information about EBS volume metrics, see Amazon CloudWatch metrics for Amazon EBS in the Amazon Elastic Compute Cloud User Guide.
Sourcepub fn get_finding_reason_codes(
&self,
) -> &Option<Vec<InstanceRecommendationFindingReasonCode>>
pub fn get_finding_reason_codes( &self, ) -> &Option<Vec<InstanceRecommendationFindingReasonCode>>
The reason for the finding classification of the instance.
Finding reason codes for instances include:
-
CPUOverprovisioned
— The instance’s CPU configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theCPUUtilization
metric of the current instance during the look-back period. -
CPUUnderprovisioned
— The instance’s CPU configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better CPU performance. This is identified by analyzing theCPUUtilization
metric of the current instance during the look-back period. -
MemoryOverprovisioned
— The instance’s memory configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing the memory utilization metric of the current instance during the look-back period. -
MemoryUnderprovisioned
— The instance’s memory configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better memory performance. This is identified by analyzing the memory utilization metric of the current instance during the look-back period.Memory utilization is analyzed only for resources that have the unified CloudWatch agent installed on them. For more information, see Enabling memory utilization with the Amazon CloudWatch Agent in the Compute Optimizer User Guide. On Linux instances, Compute Optimizer analyses the
mem_used_percent
metric in theCWAgent
namespace, or the legacyMemoryUtilization
metric in theSystem/Linux
namespace. On Windows instances, Compute Optimizer analyses theMemory % Committed Bytes In Use
metric in theCWAgent
namespace. -
EBSThroughputOverprovisioned
— The instance’s EBS throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theVolumeReadBytes
andVolumeWriteBytes
metrics of EBS volumes attached to the current instance during the look-back period. -
EBSThroughputUnderprovisioned
— The instance’s EBS throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS throughput performance. This is identified by analyzing theVolumeReadBytes
andVolumeWriteBytes
metrics of EBS volumes attached to the current instance during the look-back period. -
EBSIOPSOverprovisioned
— The instance’s EBS IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theVolumeReadOps
andVolumeWriteOps
metric of EBS volumes attached to the current instance during the look-back period. -
EBSIOPSUnderprovisioned
— The instance’s EBS IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better EBS IOPS performance. This is identified by analyzing theVolumeReadOps
andVolumeWriteOps
metric of EBS volumes attached to the current instance during the look-back period. -
NetworkBandwidthOverprovisioned
— The instance’s network bandwidth configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theNetworkIn
andNetworkOut
metrics of the current instance during the look-back period. -
NetworkBandwidthUnderprovisioned
— The instance’s network bandwidth configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network bandwidth performance. This is identified by analyzing theNetworkIn
andNetworkOut
metrics of the current instance during the look-back period. This finding reason happens when theNetworkIn
orNetworkOut
performance of an instance is impacted. -
NetworkPPSOverprovisioned
— The instance’s network PPS (packets per second) configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theNetworkPacketsIn
andNetworkPacketsIn
metrics of the current instance during the look-back period. -
NetworkPPSUnderprovisioned
— The instance’s network PPS (packets per second) configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better network PPS performance. This is identified by analyzing theNetworkPacketsIn
andNetworkPacketsIn
metrics of the current instance during the look-back period. -
DiskIOPSOverprovisioned
— The instance’s disk IOPS configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theDiskReadOps
andDiskWriteOps
metrics of the current instance during the look-back period. -
DiskIOPSUnderprovisioned
— The instance’s disk IOPS configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk IOPS performance. This is identified by analyzing theDiskReadOps
andDiskWriteOps
metrics of the current instance during the look-back period. -
DiskThroughputOverprovisioned
— The instance’s disk throughput configuration can be sized down while still meeting the performance requirements of your workload. This is identified by analyzing theDiskReadBytes
andDiskWriteBytes
metrics of the current instance during the look-back period. -
DiskThroughputUnderprovisioned
— The instance’s disk throughput configuration doesn't meet the performance requirements of your workload and there is an alternative instance type that provides better disk throughput performance. This is identified by analyzing theDiskReadBytes
andDiskWriteBytes
metrics of the current instance during the look-back period.
For more information about instance metrics, see List the available CloudWatch metrics for your instances in the Amazon Elastic Compute Cloud User Guide. For more information about EBS volume metrics, see Amazon CloudWatch metrics for Amazon EBS in the Amazon Elastic Compute Cloud User Guide.
Sourcepub fn utilization_metrics(self, input: UtilizationMetric) -> Self
pub fn utilization_metrics(self, input: UtilizationMetric) -> Self
Appends an item to utilization_metrics
.
To override the contents of this collection use set_utilization_metrics
.
An array of objects that describe the utilization metrics of the instance.
Sourcepub fn set_utilization_metrics(
self,
input: Option<Vec<UtilizationMetric>>,
) -> Self
pub fn set_utilization_metrics( self, input: Option<Vec<UtilizationMetric>>, ) -> Self
An array of objects that describe the utilization metrics of the instance.
Sourcepub fn get_utilization_metrics(&self) -> &Option<Vec<UtilizationMetric>>
pub fn get_utilization_metrics(&self) -> &Option<Vec<UtilizationMetric>>
An array of objects that describe the utilization metrics of the instance.
Sourcepub fn look_back_period_in_days(self, input: f64) -> Self
pub fn look_back_period_in_days(self, input: f64) -> Self
The number of days for which utilization metrics were analyzed for the instance.
Sourcepub fn set_look_back_period_in_days(self, input: Option<f64>) -> Self
pub fn set_look_back_period_in_days(self, input: Option<f64>) -> Self
The number of days for which utilization metrics were analyzed for the instance.
Sourcepub fn get_look_back_period_in_days(&self) -> &Option<f64>
pub fn get_look_back_period_in_days(&self) -> &Option<f64>
The number of days for which utilization metrics were analyzed for the instance.
Sourcepub fn recommendation_options(self, input: InstanceRecommendationOption) -> Self
pub fn recommendation_options(self, input: InstanceRecommendationOption) -> Self
Appends an item to recommendation_options
.
To override the contents of this collection use set_recommendation_options
.
An array of objects that describe the recommendation options for the instance.
Sourcepub fn set_recommendation_options(
self,
input: Option<Vec<InstanceRecommendationOption>>,
) -> Self
pub fn set_recommendation_options( self, input: Option<Vec<InstanceRecommendationOption>>, ) -> Self
An array of objects that describe the recommendation options for the instance.
Sourcepub fn get_recommendation_options(
&self,
) -> &Option<Vec<InstanceRecommendationOption>>
pub fn get_recommendation_options( &self, ) -> &Option<Vec<InstanceRecommendationOption>>
An array of objects that describe the recommendation options for the instance.
Sourcepub fn recommendation_sources(self, input: RecommendationSource) -> Self
pub fn recommendation_sources(self, input: RecommendationSource) -> Self
Appends an item to recommendation_sources
.
To override the contents of this collection use set_recommendation_sources
.
An array of objects that describe the source resource of the recommendation.
Sourcepub fn set_recommendation_sources(
self,
input: Option<Vec<RecommendationSource>>,
) -> Self
pub fn set_recommendation_sources( self, input: Option<Vec<RecommendationSource>>, ) -> Self
An array of objects that describe the source resource of the recommendation.
Sourcepub fn get_recommendation_sources(&self) -> &Option<Vec<RecommendationSource>>
pub fn get_recommendation_sources(&self) -> &Option<Vec<RecommendationSource>>
An array of objects that describe the source resource of the recommendation.
Sourcepub fn last_refresh_timestamp(self, input: DateTime) -> Self
pub fn last_refresh_timestamp(self, input: DateTime) -> Self
The timestamp of when the instance recommendation was last generated.
Sourcepub fn set_last_refresh_timestamp(self, input: Option<DateTime>) -> Self
pub fn set_last_refresh_timestamp(self, input: Option<DateTime>) -> Self
The timestamp of when the instance recommendation was last generated.
Sourcepub fn get_last_refresh_timestamp(&self) -> &Option<DateTime>
pub fn get_last_refresh_timestamp(&self) -> &Option<DateTime>
The timestamp of when the instance recommendation was last generated.
Sourcepub fn current_performance_risk(self, input: CurrentPerformanceRisk) -> Self
pub fn current_performance_risk(self, input: CurrentPerformanceRisk) -> Self
The risk of the current instance not meeting the performance needs of its workloads. The higher the risk, the more likely the current instance cannot meet the performance requirements of its workload.
Sourcepub fn set_current_performance_risk(
self,
input: Option<CurrentPerformanceRisk>,
) -> Self
pub fn set_current_performance_risk( self, input: Option<CurrentPerformanceRisk>, ) -> Self
The risk of the current instance not meeting the performance needs of its workloads. The higher the risk, the more likely the current instance cannot meet the performance requirements of its workload.
Sourcepub fn get_current_performance_risk(&self) -> &Option<CurrentPerformanceRisk>
pub fn get_current_performance_risk(&self) -> &Option<CurrentPerformanceRisk>
The risk of the current instance not meeting the performance needs of its workloads. The higher the risk, the more likely the current instance cannot meet the performance requirements of its workload.
Sourcepub fn effective_recommendation_preferences(
self,
input: EffectiveRecommendationPreferences,
) -> Self
pub fn effective_recommendation_preferences( self, input: EffectiveRecommendationPreferences, ) -> Self
An object that describes the effective recommendation preferences for the instance.
Sourcepub fn set_effective_recommendation_preferences(
self,
input: Option<EffectiveRecommendationPreferences>,
) -> Self
pub fn set_effective_recommendation_preferences( self, input: Option<EffectiveRecommendationPreferences>, ) -> Self
An object that describes the effective recommendation preferences for the instance.
Sourcepub fn get_effective_recommendation_preferences(
&self,
) -> &Option<EffectiveRecommendationPreferences>
pub fn get_effective_recommendation_preferences( &self, ) -> &Option<EffectiveRecommendationPreferences>
An object that describes the effective recommendation preferences for the instance.
Sourcepub fn inferred_workload_types(self, input: InferredWorkloadType) -> Self
pub fn inferred_workload_types(self, input: InferredWorkloadType) -> Self
Appends an item to inferred_workload_types
.
To override the contents of this collection use set_inferred_workload_types
.
The applications that might be running on the instance as inferred by Compute Optimizer.
Compute Optimizer can infer if one of the following applications might be running on the instance:
-
AmazonEmr
- Infers that Amazon EMR might be running on the instance. -
ApacheCassandra
- Infers that Apache Cassandra might be running on the instance. -
ApacheHadoop
- Infers that Apache Hadoop might be running on the instance. -
Memcached
- Infers that Memcached might be running on the instance. -
NGINX
- Infers that NGINX might be running on the instance. -
PostgreSql
- Infers that PostgreSQL might be running on the instance. -
Redis
- Infers that Redis might be running on the instance. -
Kafka
- Infers that Kafka might be running on the instance. -
SQLServer
- Infers that SQLServer might be running on the instance.
Sourcepub fn set_inferred_workload_types(
self,
input: Option<Vec<InferredWorkloadType>>,
) -> Self
pub fn set_inferred_workload_types( self, input: Option<Vec<InferredWorkloadType>>, ) -> Self
The applications that might be running on the instance as inferred by Compute Optimizer.
Compute Optimizer can infer if one of the following applications might be running on the instance:
-
AmazonEmr
- Infers that Amazon EMR might be running on the instance. -
ApacheCassandra
- Infers that Apache Cassandra might be running on the instance. -
ApacheHadoop
- Infers that Apache Hadoop might be running on the instance. -
Memcached
- Infers that Memcached might be running on the instance. -
NGINX
- Infers that NGINX might be running on the instance. -
PostgreSql
- Infers that PostgreSQL might be running on the instance. -
Redis
- Infers that Redis might be running on the instance. -
Kafka
- Infers that Kafka might be running on the instance. -
SQLServer
- Infers that SQLServer might be running on the instance.
Sourcepub fn get_inferred_workload_types(&self) -> &Option<Vec<InferredWorkloadType>>
pub fn get_inferred_workload_types(&self) -> &Option<Vec<InferredWorkloadType>>
The applications that might be running on the instance as inferred by Compute Optimizer.
Compute Optimizer can infer if one of the following applications might be running on the instance:
-
AmazonEmr
- Infers that Amazon EMR might be running on the instance. -
ApacheCassandra
- Infers that Apache Cassandra might be running on the instance. -
ApacheHadoop
- Infers that Apache Hadoop might be running on the instance. -
Memcached
- Infers that Memcached might be running on the instance. -
NGINX
- Infers that NGINX might be running on the instance. -
PostgreSql
- Infers that PostgreSQL might be running on the instance. -
Redis
- Infers that Redis might be running on the instance. -
Kafka
- Infers that Kafka might be running on the instance. -
SQLServer
- Infers that SQLServer might be running on the instance.
Sourcepub fn instance_state(self, input: InstanceState) -> Self
pub fn instance_state(self, input: InstanceState) -> Self
The state of the instance when the recommendation was generated.
Sourcepub fn set_instance_state(self, input: Option<InstanceState>) -> Self
pub fn set_instance_state(self, input: Option<InstanceState>) -> Self
The state of the instance when the recommendation was generated.
Sourcepub fn get_instance_state(&self) -> &Option<InstanceState>
pub fn get_instance_state(&self) -> &Option<InstanceState>
The state of the instance when the recommendation was generated.
Appends an item to tags
.
To override the contents of this collection use set_tags
.
A list of tags assigned to your Amazon EC2 instance recommendations.
A list of tags assigned to your Amazon EC2 instance recommendations.
A list of tags assigned to your Amazon EC2 instance recommendations.
Sourcepub fn external_metric_status(self, input: ExternalMetricStatus) -> Self
pub fn external_metric_status(self, input: ExternalMetricStatus) -> Self
An object that describes Compute Optimizer's integration status with your external metrics provider.
Sourcepub fn set_external_metric_status(
self,
input: Option<ExternalMetricStatus>,
) -> Self
pub fn set_external_metric_status( self, input: Option<ExternalMetricStatus>, ) -> Self
An object that describes Compute Optimizer's integration status with your external metrics provider.
Sourcepub fn get_external_metric_status(&self) -> &Option<ExternalMetricStatus>
pub fn get_external_metric_status(&self) -> &Option<ExternalMetricStatus>
An object that describes Compute Optimizer's integration status with your external metrics provider.
Sourcepub fn current_instance_gpu_info(self, input: GpuInfo) -> Self
pub fn current_instance_gpu_info(self, input: GpuInfo) -> Self
Describes the GPU accelerator settings for the current instance type.
Sourcepub fn set_current_instance_gpu_info(self, input: Option<GpuInfo>) -> Self
pub fn set_current_instance_gpu_info(self, input: Option<GpuInfo>) -> Self
Describes the GPU accelerator settings for the current instance type.
Sourcepub fn get_current_instance_gpu_info(&self) -> &Option<GpuInfo>
pub fn get_current_instance_gpu_info(&self) -> &Option<GpuInfo>
Describes the GPU accelerator settings for the current instance type.
Sourcepub fn idle(self, input: InstanceIdle) -> Self
pub fn idle(self, input: InstanceIdle) -> Self
Describes if an Amazon EC2 instance is idle.
Sourcepub fn set_idle(self, input: Option<InstanceIdle>) -> Self
pub fn set_idle(self, input: Option<InstanceIdle>) -> Self
Describes if an Amazon EC2 instance is idle.
Sourcepub fn get_idle(&self) -> &Option<InstanceIdle>
pub fn get_idle(&self) -> &Option<InstanceIdle>
Describes if an Amazon EC2 instance is idle.
Sourcepub fn build(self) -> InstanceRecommendation
pub fn build(self) -> InstanceRecommendation
Consumes the builder and constructs a InstanceRecommendation
.
Trait Implementations§
Source§impl Clone for InstanceRecommendationBuilder
impl Clone for InstanceRecommendationBuilder
Source§fn clone(&self) -> InstanceRecommendationBuilder
fn clone(&self) -> InstanceRecommendationBuilder
1.0.0 · Source§const fn clone_from(&mut self, source: &Self)
const fn clone_from(&mut self, source: &Self)
source
. Read moreSource§impl Default for InstanceRecommendationBuilder
impl Default for InstanceRecommendationBuilder
Source§fn default() -> InstanceRecommendationBuilder
fn default() -> InstanceRecommendationBuilder
Source§impl PartialEq for InstanceRecommendationBuilder
impl PartialEq for InstanceRecommendationBuilder
Source§fn eq(&self, other: &InstanceRecommendationBuilder) -> bool
fn eq(&self, other: &InstanceRecommendationBuilder) -> bool
self
and other
values to be equal, and is used by ==
.impl StructuralPartialEq for InstanceRecommendationBuilder
Auto Trait Implementations§
impl Freeze for InstanceRecommendationBuilder
impl RefUnwindSafe for InstanceRecommendationBuilder
impl Send for InstanceRecommendationBuilder
impl Sync for InstanceRecommendationBuilder
impl Unpin for InstanceRecommendationBuilder
impl UnwindSafe for InstanceRecommendationBuilder
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Source§impl<T> CloneToUninit for Twhere
T: Clone,
impl<T> CloneToUninit for Twhere
T: Clone,
Source§impl<T> Instrument for T
impl<T> Instrument for T
Source§fn instrument(self, span: Span) -> Instrumented<Self>
fn instrument(self, span: Span) -> Instrumented<Self>
Source§fn in_current_span(self) -> Instrumented<Self>
fn in_current_span(self) -> Instrumented<Self>
Source§impl<T> IntoEither for T
impl<T> IntoEither for T
Source§fn into_either(self, into_left: bool) -> Either<Self, Self>
fn into_either(self, into_left: bool) -> Either<Self, Self>
self
into a Left
variant of Either<Self, Self>
if into_left
is true
.
Converts self
into a Right
variant of Either<Self, Self>
otherwise. Read moreSource§fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
self
into a Left
variant of Either<Self, Self>
if into_left(&self)
returns true
.
Converts self
into a Right
variant of Either<Self, Self>
otherwise. Read moreSource§impl<T> Paint for Twhere
T: ?Sized,
impl<T> Paint for Twhere
T: ?Sized,
Source§fn fg(&self, value: Color) -> Painted<&T>
fn fg(&self, value: Color) -> Painted<&T>
Returns a styled value derived from self
with the foreground set to
value
.
This method should be used rarely. Instead, prefer to use color-specific
builder methods like red()
and
green()
, which have the same functionality but are
pithier.
§Example
Set foreground color to white using fg()
:
use yansi::{Paint, Color};
painted.fg(Color::White);
Set foreground color to white using white()
.
use yansi::Paint;
painted.white();
Source§fn bright_black(&self) -> Painted<&T>
fn bright_black(&self) -> Painted<&T>
Source§fn bright_red(&self) -> Painted<&T>
fn bright_red(&self) -> Painted<&T>
Source§fn bright_green(&self) -> Painted<&T>
fn bright_green(&self) -> Painted<&T>
Source§fn bright_yellow(&self) -> Painted<&T>
fn bright_yellow(&self) -> Painted<&T>
Source§fn bright_blue(&self) -> Painted<&T>
fn bright_blue(&self) -> Painted<&T>
Source§fn bright_magenta(&self) -> Painted<&T>
fn bright_magenta(&self) -> Painted<&T>
Source§fn bright_cyan(&self) -> Painted<&T>
fn bright_cyan(&self) -> Painted<&T>
Source§fn bright_white(&self) -> Painted<&T>
fn bright_white(&self) -> Painted<&T>
Source§fn bg(&self, value: Color) -> Painted<&T>
fn bg(&self, value: Color) -> Painted<&T>
Returns a styled value derived from self
with the background set to
value
.
This method should be used rarely. Instead, prefer to use color-specific
builder methods like on_red()
and
on_green()
, which have the same functionality but
are pithier.
§Example
Set background color to red using fg()
:
use yansi::{Paint, Color};
painted.bg(Color::Red);
Set background color to red using on_red()
.
use yansi::Paint;
painted.on_red();
Source§fn on_primary(&self) -> Painted<&T>
fn on_primary(&self) -> Painted<&T>
Source§fn on_magenta(&self) -> Painted<&T>
fn on_magenta(&self) -> Painted<&T>
Source§fn on_bright_black(&self) -> Painted<&T>
fn on_bright_black(&self) -> Painted<&T>
Source§fn on_bright_red(&self) -> Painted<&T>
fn on_bright_red(&self) -> Painted<&T>
Source§fn on_bright_green(&self) -> Painted<&T>
fn on_bright_green(&self) -> Painted<&T>
Source§fn on_bright_yellow(&self) -> Painted<&T>
fn on_bright_yellow(&self) -> Painted<&T>
Source§fn on_bright_blue(&self) -> Painted<&T>
fn on_bright_blue(&self) -> Painted<&T>
Source§fn on_bright_magenta(&self) -> Painted<&T>
fn on_bright_magenta(&self) -> Painted<&T>
Source§fn on_bright_cyan(&self) -> Painted<&T>
fn on_bright_cyan(&self) -> Painted<&T>
Source§fn on_bright_white(&self) -> Painted<&T>
fn on_bright_white(&self) -> Painted<&T>
Source§fn attr(&self, value: Attribute) -> Painted<&T>
fn attr(&self, value: Attribute) -> Painted<&T>
Enables the styling Attribute
value
.
This method should be used rarely. Instead, prefer to use
attribute-specific builder methods like bold()
and
underline()
, which have the same functionality
but are pithier.
§Example
Make text bold using attr()
:
use yansi::{Paint, Attribute};
painted.attr(Attribute::Bold);
Make text bold using using bold()
.
use yansi::Paint;
painted.bold();
Source§fn rapid_blink(&self) -> Painted<&T>
fn rapid_blink(&self) -> Painted<&T>
Source§fn quirk(&self, value: Quirk) -> Painted<&T>
fn quirk(&self, value: Quirk) -> Painted<&T>
Enables the yansi
Quirk
value
.
This method should be used rarely. Instead, prefer to use quirk-specific
builder methods like mask()
and
wrap()
, which have the same functionality but are
pithier.
§Example
Enable wrapping using .quirk()
:
use yansi::{Paint, Quirk};
painted.quirk(Quirk::Wrap);
Enable wrapping using wrap()
.
use yansi::Paint;
painted.wrap();
Source§fn clear(&self) -> Painted<&T>
👎Deprecated since 1.0.1: renamed to resetting()
due to conflicts with Vec::clear()
.
The clear()
method will be removed in a future release.
fn clear(&self) -> Painted<&T>
resetting()
due to conflicts with Vec::clear()
.
The clear()
method will be removed in a future release.Source§fn whenever(&self, value: Condition) -> Painted<&T>
fn whenever(&self, value: Condition) -> Painted<&T>
Conditionally enable styling based on whether the Condition
value
applies. Replaces any previous condition.
See the crate level docs for more details.
§Example
Enable styling painted
only when both stdout
and stderr
are TTYs:
use yansi::{Paint, Condition};
painted.red().on_yellow().whenever(Condition::STDOUTERR_ARE_TTY);